Introduction to Computing and Programming in Python

Introduction to Computing and Programming in Python, 3e, uses multimedia applications to motivate introductory computer science majors or non-majors. The book's hands-on approach shows how programs can be used to build multimedia computer science applications that include sound, graphics, music, pictures, and movies. The students learn a key set of computer science tools and topics, as well as programming skills; such as how to design and use algorithms, and practical software engineering methods. The book also includes optional coverage of HCI, as well as rudimentary data structures and databases using the user-friendly Python language for implementation. Authors Guzdial and Ericson also demonstrate how to communicate compatibly through networks and do concurrent programming.

Table of Contents:
Preface to the Third Edition xv
Preface to the Second Edition xvii
Preface to the First Edition xix
About the Authors xxv
1 INTRODUCTION 1
1 Introduction to Computer Science and Media Computation 3
1.1 What Is Computer Science About? 3
1.2 Programming Languages 6
1.3 What Computers Understand 8
1.4 Media Computation: Why Digitize Media? 11
1.5 Computer Science for Everyone 12
1.5.1 It’s About Communication 12
1.5.2 It’s About Process 12

2 Introduction to Programming 16
2.1 Programming Is About Naming 16
2.1.1 Files and Their Names 18
2.2 Programming in Python 19
2.3 Programming in JES 20
2.4 Media Computation in JES 21
2.4.1 Showing a Picture 25
2.4.2 Playing a Sound 27
2.4.3 Naming Values 28
2.5 Making a Program 31
2.5.1 Variable Recipes: Real Math-Like Functions That Take Input 34

3 Modifying Pictures Using Loops 40
3.1 How Pictures Are Encoded 41
3.2 Manipulating Pictures 46
3.2.1 Exploring Pictures 51
3.3 Changing Color Values 53
3.3.1 Using Loops in Pictures 53
3.3.2 Increasing/Decreasing Red (Green, Blue) 55
3.3.3 Testing the Program: Did That Really Work? 60
3.3.4 Changing One Color at a Time 61
3.4 Creating a Sunset 62
3.4.1 Making Sense of Functions 63
3.5 Lightening and Darkening 67
3.6 Creating a Negative 68
3.7 Converting to Grayscale 69

4 Modifying Pixels in a Range 75
4.1 Copying Pixels 75
4.1.1 Looping Across the Pixels with range 76
4.2 Mirroring a Picture 78
4.3 Copying and Transforming Pictures 86
4.3.1 Copying 86
4.3.2 Creating a Collage 94
4.3.3 General Copying 96
4.3.4 Rotation 98
4.3.5 Scaling 100

5 Picture Techniques with Selection and Combination 107
5.1 Replacing Colors: Red-Eye, Sepia Tones, and Posterizing 108
5.1.1 Reducing Red-Eye 111
5.1.2 Sepia-Toned and Posterized Pictures: Using Conditionals to Choose the Color 113
5.2 Combining Pixels: Blurring 118
5.3 Comparing Pixels: Edge Detection 119
5.4 Blending Pictures 122
5.5 Background Subtraction 125
5.6 Chromakey 127
5.7 Drawing on Images 131
5.7.1 Drawing with Drawing Commands 132
5.7.2 Vector and Bitmap Representations 133
5.8 Selecting Without Re-Testing 135
5.9 Programs as Specifying Drawing Process 136
5.9.1 Why Do We Write Programs? 139

2 SOUND 143
6 Modifying Sounds Using Loops 145
6.1 How Sound Is Encoded 145
6.1.1 The Physics of Sound 145
6.1.2 Exploring How Sounds Look 149
6.1.3 Encoding the Sound 151
6.1.4 Binary Numbers and Two’s Complement 153
6.1.5 Storing Digitized Sounds 154
6.2 Manipulating Sounds 156
6.2.1 Open Sounds and Manipulating Samples 156
6.2.2 Using the JES MediaTools 159
6.2.3 Looping 161
6.3 Changing the Volume of Sounds 161
6.3.1 Increasing Volume 161
6.3.2 Did That Really Work? 162
6.3.3 Decreasing Volume 166
6.3.4 Making Sense of Functions, in Sounds 167
6.4 Normalizing Sounds 167
6.4.1 Generating Clipping 169

7 Modifying Samples in a Range 174
7.1 Manipulating Different Sections of the Sound Differently 174
7.2 Splicing Sounds 177
7.3 General Clip and Copy 183
7.4 Reversing Sounds 186
7.5 Mirroring 187
7.6 On Functions and Scope 188

8 Making Sounds by Combining Pieces 193
8.1 Composing Sounds Through Addition 193
8.2 Blending Sounds 195
8.3 Creating an Echo 196
8.3.1 Creating Multiple Echoes 197
8.3.2 Creating Chords 198
8.4 How Sampling Keyboards Work 198
8.4.1 Sampling as an Algorithm 202
8.5 Additive Synthesis 203
8.5.1 Making SineWaves 203
8.5.2 Adding SineWaves Together 205
8.5.3 Checking Our Result 206
8.5.4 SquareWaves 207
8.5.5 TriangularWaves 210
8.6 Modern Music Synthesis 211
8.6.1 MP3 212
8.6.2 MIDI 212

9 Building Bigger Programs 216
9.1 Designing Programs Top-Down 217
9.1.1 A Top-Down Design Example 218
9.1.2 Designing the Top-Level Function 219
9.1.3 Writing the Subfunctions 221
9.2 Designing Programs Bottom-Up 225
9.2.1 An Example Bottom-Up Process 226
9.3 Testing Your Program 226
9.3.1 Testing the Edge Conditions 228
9.4 Tips on Debugging 228
9.4.1 Finding which Statement to Worry About 230
9.4.2 Seeing the Variables 230
9.4.3 Debugging the Adventure Game 232
9.5 Algorithms and Design 235
9.6 Running Programs Outside of JES 236

3 TEXT, FILES,NETWORKS,DATABASES, AND UNIMEDIA 242
10 Creating and Modifying Text 244
10.1 Text as Unimedia 244
10.2 Strings: Making and Manipulating Strings 245
10.3 Manipulating Parts of Strings 248
10.3.1 String Methods: Introducing Objects and Dot Notation 248
10.3.2 Lists: Powerful, Structured Text 251
10.3.3 Strings Have No Font 253
10.4 Files: Places to Put Your Strings and Other Stuff 254
10.4.1 Opening and Manipulating Files 255
10.4.2 Generating Form Letters 257
10.4.3 Writing Out Programs 258
10.5 The Python Standard Library 262
10.5.1 More on Import and Your Own Modules 263
10.5.2 Another Fun Module: Random 263
10.5.3 A Sampling of Python Standard Libraries 265

11 Advanced Text Techniques: Web and Information 270
11.1 Networks: Getting Our Text from the Web 270
11.2 Using Text to Shift Between Media 277
11.3 Moving Information Between Media 280
11.4 Using Lists As Structured Text for Media Representations 282
11.5 Hiding Information in a Picture 284

12 Making Text for the Web 289
12.1 HTML: The Notation of the Web 289
12.2 Writing Programs to Generate HTML 294
12.3 Databases: A Place to Store Our Text 299
12.3.1 Relational Databases 301
12.3.2 An Example Relational Database Using HashTables 302
12.3.3 Working with SQL 304
12.3.4 Using a Database to Build Web Pages 307

4 MOVIES 311
13 Creating and Modifying Movies 313
13.1 Generating Animations 314
13.2 Working with Video Source 322
13.2.1 Video Manipulating Examples 323
13.3 Building a Video Effect Bottom-Up 326

5 TOPICS IN COMPUTER SCIENCE 333
14 Speed 335
14.1 Focusing on Computer Science 335
14.2 What Makes Programs Fast? 335
14.2.1 What Computers Really Understand 336
14.2.2 Compilers and Interpreters 337
14.2.3 What Limits Computer Speed? 341
14.2.4 Does It Really Make a Difference? 343
14.2.5 Making Searching Faster 345
14.2.6 Algorithms That Never Finish or Can’t Be Written 347
14.2.7 Why Is Photoshop Faster Than JES? 349
14.3 What Makes a Computer Fast? 349
14.3.1 Clock Rates and Actual Computation 350
14.3.2 Storage: What Makes a Computer Slow? 351
14.3.3 Display 352

15 Functional Programming 355
15.1 Using Functions to Make Programming Easier 355
15.2 Functional Programming with Map and Reduce 358
15.3 Functional Programming for Media 362
15.3.1 Media Manipulation Without Changing State 363
15.4 Recursion: A Powerful Idea 364
15.4.1 Recursive Directory Traversals 369
15.4.2 Recursive Media Functions 371

16 Object-Oriented Programming 376
16.1 History of Objects 376
16.2 Working with Turtles 378
16.2.1 Classes and Objects 378
16.2.2 Sending Messages to Objects 379
16.2.3 Objects Control Their State 381
16.3 Teaching Turtles New Tricks 383
16.3.1 Overriding an Existing Turtle Method 385
16.3.2 Using Turtles for More 386
16.4 An Object-Oriented Slide Show 390
16.4.1 Making the Slide Class More Object-Oriented 393
16.5 Object-Oriented Media 395
16.6 Joe the Box 400
16.7 Why Objects? 401

APPENDIX 406
A Quick Reference to Python 406
A.1 Variables 406
A.2 Function Creation 407
A.3 Loops and Conditionals 407
A.4 Operators and Representation Functions 408
A.5 Numeric Functions 409
A.6 Sequence Operations 409
A.7 String Escapes 409
A.8 Useful String Methods 409
A.9 Files 410
A.10 Lists 410
A.11 Dictionaries, Hash Tables, or Associative Arrays 410
A.12 External Modules 410
A.13 Classes 411
A.14 Functional Methods 411
Bibliography 412
Index 415



About the Author :
Barbara Ericson is a research scientist and the Director of Computing Outreach for the College of Computing at Georgia Tech. She has been working on improving introductory computing education for over 5 years. She enjoys the diversity of the types of problems she has worked on over the years in computing including computer graphics, artificial intelligence, medicine, and object-oriented programming.

Mark Guzdial is a Professor in the School of Interactive Computing at Georgia Tech.  An award-winning teacher and active researcher in computing education, he holds a joint Ph.D. In Education and Computer Science from the University of Michigan. Dr. Guzdial directs Project “Georgia Computes!” which is an NSF funded alliance to improve computing education from pre-teen years to undergraduates.  He is a member of the ACM Education Board and is a frequent contributor to the ACM SIGCSE (Computer Science Education) Symposium.

Barbara Ericson and Mark Guzdial, are recipients of the 2010 Karl V. Karlstom Outstanding Educator Award for their contributions to broadening participation in computing. They created the Media Computation (MediaComp) approach, which motivates students to write programs that manipulate and create digital media, such as pictures, sounds, and videos. Now in use in nearly 200 schools around the world, this contextualized approach to introductory Computer Science attracts students not motivated by classical algorithmic problems addressed in traditional computer science education. They also lead “Georgia Computes!” an NSF-funded statewide alliance to increase the number and diversity of students in computing education across all of Georgia.  Barbara Ericson directs the Institute for Computing Education at Georgia Tech. Mark Guzdial is director of the Contextualized Support for Learning at Georgia Tech.  Together they have written three textbooks using the MediaComp approach to engage and inspire student learning in computing. The Karlstrom Award recognizes educators who advanced new teaching methodologies; effected new curriculum development in Computer Science and Engineering; or contributed to ACM’s educational mission.